Without
technical progress and agricultural intensification and with current rates of
population growth, agriculture would need an area equivalent to one half and
two-third of the current terrestrial land area by 2030 and 2070, respectively,
in order to maintain current food consumption levels per capita. Considering
the evolution of technology, agricultural management, and food consumption
preferences; the OECD-FAO Agricultural Outlook projects global increases in
cropland requirements of about 9% by 2019. Existing projections of future
irrigation water consumption between 1995 and 2025 (e.g., Molden, 2007; Postel, 1998; Rosegrant et al., 2002b) differ substantially and range from minus
17% to plus 228%. This variation is due to methodological and data differences
as described in Sauer et al. (2010).
The second
argument supporting a global dimension of food production challenges is that
although some regions experience more problems than others, today’s societies
are increasingly connected. Globalization has opened the door to more
international trade. Thus, regional commodity supply shortage or surplus can be
transferred to and mitigated by world markets. Furthermore, globalization has
also influenced governmental regulations. National land use related policies
are increasingly embedded in international policies.
Since the
establishment of the United Nations in 1945, many different international
treaties have been adopted, which may particularly affect global food
production and distribution. Environmental treaties relevant to food production
include the convention on wetlands (RAMSAR convention), the Climate Change
convention, and the convention on biological diversity (CBD convention).
These
treaties may limit possible expansion of agricultural land. However, expansion
of cropland might be necessary to fulfill the eight Millennium Development
Goals defined by the world leaders at the United Nations Millennium Summit in
2002 since they include targets for the reduction of hunger and malnutrition.
A third argument
is that the cumulative impacts of local land use decisions may cause
significant global environmental feedback, foremost through climate change (Alcamo et al., 2003; Foley et al., 2005; Tilman et al.,
2001). There are
both positive and negative agricultural impacts which influence the
availability and fertility of land (Ramankutty et al., 2002), the length of the growing season (Lobell et al., 2008), fresh water endowments, pest occurrences,
CO2 fertilization, and the frequency of extreme events related to
draughts, flooding, fire, and frost.
Although global commodity trade and
environmental policies are important drivers for resource utilization, a
variety of additional factors influence the net impact of future development on
land use and food supply. These factors include technical progress, land use
intensities, land quality variations, resource endowments, and food demand
characteristics. Technical progress and management intensification generally
reduce land scarcity.
While
improved technologies shift the production possibility frontier outwards,
intensification moves production along a frontier by substituting one resource
with another (Samuelson, 1948). Agricultural production can be intensified by employing more
water, fertilizer, pesticides, machinery, or labor. While intensification is
often measured relative to the fixed production factor land, it may also be
related to output. In contrast to technical change, intensification increases
at least one input requirement per unit of output. Irrigation, for example,
uses per calorie less land but more water, fertilizer, and/or capital.
The
variation of land quality also interacts with development. Population growth
increases food demand and therefore the demand for agricultural land. Since
rationally acting agents use the economically most suitable resource first,
additional agricultural land is likely to be less profitable. In addition,
population growth increases predominantly urban land areas (United Nations, 2004). This expansion potentially removes high
quality agricultural areas since cities are usually built on fertile land (von ThĂĽnen, 1875).
Furthermore,
increased agricultural intensity due to population growth may increase land degradation
over time. This could trigger a positive feedback loop where increased
degradation leads to more degradation through intensification. Fourth, income
growth especially in low income regions raises demand for animal based food
more than demand for plant based food. Since animal food production involves an
additional element in the food chain, it may in some cases increase land
requirements per calorie by a factor of 10 or more relative to plant food (Gerbens-Leenes and Nonhebel, 2005). Thus, an increased demand of animal food
is likely to increase total agricultural land use and management intensities
with the above described implications.
To
assess the complex interdependencies between population growth, economic and
technological development, and the associated relative scarcities of land and
water, we use the Global Biomass Optimization Model (GLOBIOM). GLOBIOM is a
mathematical programming model of the global agricultural and forest sectors.
Data, concept and mathematical structure of this model are described in HavlĂk et al. (in press) and at www.globiom.org. The core model equations are given in
mathematical notation in Appendix.
The objective
function of GLOBIOM simulates the global agricultural and forest market
equilibrium by maximizing economic surplus over all included regions and
commodities subject to restrictions on resource endowments, technologies, and
policies. The scope and resolution of regions, commodities, management options,
and resources is shown in Tables 1 and 2. Particularly,
agricultural and forest product markets are represented by 28 international regions
covering the entire world. The definition of regions is consistent with 11
larger regions used in energy (Messner and Strubegger, 1995) and pollution abatement models (Amann, 2004) of IIASA’s Greenhouse Gas Initiative and with the definition
of more detailed regions from the POLES model (Criqui et al., 1999). Common region definitions facilitate the
linkage of GLOBIOM with energy models in the context of climate and energy
sustainability assessments.
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